| | |
| | | import torch |
| | | import torch.multiprocessing |
| | | import torch.nn |
| | | import torch.optim |
| | | |
| | | from funasr.schedulers.noam_lr import NoamLR |
| | | from funasr.schedulers.tri_stage_scheduler import TriStageLR |
| | | from funasr.schedulers.warmup_lr import WarmupLR |
| | | |
| | | scheduler_choices = dict( |
| | | ReduceLROnPlateau=torch.optim.lr_scheduler.ReduceLROnPlateau, |
| | | lambdalr=torch.optim.lr_scheduler.LambdaLR, |
| | | steplr=torch.optim.lr_scheduler.StepLR, |
| | | multisteplr=torch.optim.lr_scheduler.MultiStepLR, |
| | | exponentiallr=torch.optim.lr_scheduler.ExponentialLR, |
| | | CosineAnnealingLR=torch.optim.lr_scheduler.CosineAnnealingLR, |
| | | noamlr=NoamLR, |
| | | warmuplr=WarmupLR, |
| | | tri_stage=TriStageLR, |
| | | cycliclr=torch.optim.lr_scheduler.CyclicLR, |
| | | onecyclelr=torch.optim.lr_scheduler.OneCycleLR, |
| | | CosineAnnealingWarmRestarts=torch.optim.lr_scheduler.CosineAnnealingWarmRestarts, |
| | | ) |